\hypertarget{pgpr__ppitc_8h}{\section{src/pgpr\+\_\+ppitc.h File Reference}
\label{pgpr__ppitc_8h}\index{src/pgpr\+\_\+ppitc.\+h@{src/pgpr\+\_\+ppitc.\+h}}
}


This file provides the predictor (\hyperlink{classpgpr__ppitc}{pgpr\+\_\+ppitc}) with parallel P\+I\+T\+C Gaussian Process.  


{\ttfamily \#include \char`\"{}mpi.\+h\char`\"{}}\\*
{\ttfamily \#include \char`\"{}pgpr\+\_\+util.\+h\char`\"{}}\\*
{\ttfamily \#include \char`\"{}pgpr\+\_\+cov.\+h\char`\"{}}\\*
{\ttfamily \#include \char`\"{}pgpr\+\_\+chol.\+h\char`\"{}}\\*
\subsection*{Classes}
\begin{DoxyCompactItemize}
\item 
class \hyperlink{classpgpr__ppitc}{pgpr\+\_\+ppitc}
\begin{DoxyCompactList}\small\item\em This class provides the regression function using P\+I\+T\+C Approximation,implemented in a parallel manner. \end{DoxyCompactList}\end{DoxyCompactItemize}


\subsection{Detailed Description}
This file provides the predictor (\hyperlink{classpgpr__ppitc}{pgpr\+\_\+ppitc}) with parallel P\+I\+T\+C Gaussian Process. 

